def split(u, v, points):
# return points on left side of UV
return [p for p in points if np.cross(p - u, v - u) < 0]
def extend(u, v, points):
if not points:
return []
# find furthest point W, and split search to WV, UW
w = min(points, key=lambda p: np.cross(p - u, v - u))
p1, p2 = split(w, v, points), split(u, w, points)
return extend(w, v, p1) + [w] + extend(u, w, p2)
def calc_convex_hull(points):
# find two hull points, U, V, and split to left and right search
u = min(points, key=lambda p: p[0])
v = max(points, key=lambda p: p[0])
left, right = split(u, v, points), split(v, u, points)
# find convex hull on each side
return [v] + extend(u, v, left) + \
[u] + extend(v, u, right) + [v]
convex_hull_x_datasets = []
convex_hull_y_datasets = []
for i in range(0, len(datasets)):
points = []
for j in range(0, len(time_msec_datasets[i])):
points.append(np.array([time_msec_datasets[i][j], contraction_length_msec_datasets[i][j]]))
convex_hull = calc_convex_hull(points)
convex_hull_x =[]
convex_hull_y =[]
for point in convex_hull:
convex_hull_x.append(point[0])
convex_hull_y.append(point[1])
convex_hull_x_datasets.append(convex_hull_x)
convex_hull_y_datasets.append(convex_hull_y)
for i in range(0, len(datasets)):
plt.subplot(SUB_PLOT_ROWS, SUB_PLOT_COLS, i+1)
plt.plot(convex_hull_x_datasets[i], convex_hull_y_datasets[i], '-', color='red', label="convex hull of contraction duration vs. time")
plot_datasets()
